Managing flight paths of a soaring aircraft

ABSTRACT

Disclosed is a novel system and method for adjusting a flight path of an aircraft. The method begins with computing a flight path of an aircraft from a starting point to an ending point which incorporates predicted weather effects at different points in space and time. An iterative loop is entered for the flight path. Each of the following steps are performed in the iterative loop. First lift data is accessed from a fine-grain weather model associated with a geographic region of interest. The lift data is data to calculate a force that directly opposes a weight of the aircraft. In addition, lift data is accessed from sensors coupled to the aircraft. The lift data is one or more of 1) thermal data, 2) ridge lift data, 3) wave lift data, 3) convergence lift data, and 4) a dynamic soaring lift data. Numerous embodiments are disclosed.

BACKGROUND

The present invention generally relates to flight paths of aircraft andmore specifically to flight path of a soaring aircraft as it relates tolift forces.

Initially soaring and gliding was used to increase the duration offlights. Soon however, pilots attempted flights away from the place oflaunch. Improvements in aerodynamics and in the understanding of weatherphenomena have allowed greater distances at higher average speeds. Longdistances are now flown using any of the main sources of rising air:ridge lift, thermals and lee waves. When conditions are favorable,experienced pilots can now fly hundreds of kilometers before returningto their home airfields.

Gliders are used for tasks such as search and rescue, surveillance,transportation, and pleasure. Gliders are reliant on meteorologicalconditions to provide lift; subsequently the optimal route from A to Bis often not direct.

SUMMARY

Disclosed is a novel system and method for flight path calculation basedon fine-grained weather forecasting, nowcasting, and path searching.Based on continuously updated forecasts, the presently claimed inventiondetermines a path to destination using detailed fine-grained informationon current and future lift locations and wind direction.

In one example, a computer-implemented method for adjusting a flightpath of an aircraft is described. The method begins with computing aflight path of an aircraft from a starting point to an ending pointwhich incorporates predicted weather effects at different points inspace and time. An iterative loop is entered for the flight path. Eachof the following steps are performed in the iterative loop. First liftdata is accessed from a fine-grain weather model associated with ageographic region of interest. The lift data is data used to calculate aforce that directly opposes a weight of the aircraft. In addition, liftdata may be accessed from sensors coupled to the aircraft. The lift datais one or more of 1) thermal data where air rises due to temperature, 2)ridge lift data where air is forced upwards by a slope, 3) wave liftdata where a mountain produces a standing wave, 3) convergence lift datawhere two air masses meet, and 4) a dynamic soaring lift data wheredifferences in wind speeds at various altitudes is used.

Adjustments to the flight path are calculated based on a combination ofthe lift data from the fine-grain weather model and the lift data fromsensors and other weather data. In one example, crowdsourcing data isalso used. These calculations can be performed on the aircraft, on otheraircraft, ground stations, or a combination thereof. Also, adjustmentsto flight path can also be received from other aircraft. The flight pathis adjusted based upon the adjustments that have been calculated. Thisflight path information, in another example is shared with otheraircraft.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying figures wherein reference numerals refer to identicalor functionally similar elements throughout the separate views, andwhich together with the detailed description below are incorporated inand form part of the specification, serve to further illustrate variousembodiments and to explain various principles and advantages all inaccordance with the present invention, in which:

FIG. 1 is a diagram of a soaring aircraft using thermal lift;

FIG. 2 is a diagram of a soaring aircraft using ridge lift;

FIG. 3 is a diagram of a soaring aircraft using convergence lift;

FIG. 4 is a diagram of a soaring aircraft using wave lift;

FIG. 5 is a diagram of a soaring aircraft using dynamic lift;

FIG. 6 is a diagram of three aircraft sharing lift data from varioussources;

FIG. 7 is a diagram of the major sources of data input for a flight pathprocessor;

FIG. 8 is a table of lift data from various sources, locations, and timeperiods;

FIG. 9 is a flow chart of processing lift data; and

FIG. 10 is a block diagram of an information processing system that maybe used as a flight path processor.

DETAILED DESCRIPTION

As required, detailed embodiments are disclosed herein; however, it isto be understood that the disclosed embodiments are merely examples andthat the systems and methods described below can be embodied in variousforms. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representative basis for teaching one skilled in theart to variously employ the present subject matter in virtually anyappropriately detailed structure and function. Further, the terms andphrases used herein are not intended to be limiting, but rather, toprovide an understandable description of the concepts.

The description of the present invention has been presented for purposesof illustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

An important component to the claimed invention is “fine-grained weatherforecasting.” Predicting the weather accurately is a hard enoughcomputing problem. Predicting the weather for a specific location downto a square kilometer—and how it will affect the people andinfrastructure there—is a problem of a much different sort. And it'sthat sort of “hyper-local” forecasting that IBM's Deep Thunder provides.

Precision weather prediction or “fine-grained weather” forecasting wasoriginally set up in the IBM in 1996. Currently the IBM technology isknown as “Deep Thunder” See online URL(en.wikipedia.org/wiki/IBM_Deep_Thunder). Deep Thunder provides local,high-resolution weather predictions customized to weather-sensitivespecific business operations. For example, it could be used to predictthe wind velocity at an Olympic diving platform, or where there will beflooding and predict where mudslides might be triggered by severestorms. or damaged power lines up to 84 hours in advance. Unlike thelong-term strategic weather forecasts that many companies rely on toplan business, Deep Thunder is focused on forecasts in small ageographic area with a very fine time granularity. For example, in 2001,IBM set up a test bed in the New York City metropolitan area. A 3D gridof thousands of blocks, each one cubic kilometer in size was setup.Calculations could be run on each cube of the grid to generate verylocal and precise predictions. The team also began working on the kindof modeling, forecasting, and data visualization innovations that couldhelp a business make smarter logistical, planning and operationaldecisions, faster and with more confidence.

The presently claimed invention provides a novel system and method forflight path calculation based on fine-grained weather forecasting,nowcasting, and path searching. Based on continuously updated forecastswe are able to find a path to destination using detailed fine-grainedinformation on current and future lift locations and wind direction.

NON-LIMITING DEFINITIONS

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise.

The term “aircraft” is a machine that is able to fly by gaining supportfrom the air. Aircraft includes unpowered gliders, balloons, dirigibles,and kites. Aircraft also includes powered fixed winged designs with oneor more engines to produce thrust. The engines can run on fuel or bebattery powered. Aircraft also includes powered rotorcrafts includinghelicopters.

The terms “comprises” and/or “comprising,” specify the presence ofstated features, steps, operations, elements, and/or components, but donot preclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof.

The term “crowdsourcing data” is data from a group of individualstypically that elect to share data for a specific flight path.

The term “fine-grained weather model” also known as “microscalemeteorology” or “hyper-local forecasting” means a weather model is amodel that is able to forecast weather to a small specific geographicregion i.e., less than a kilometer for an immediate time period Timeperiods of a few seconds to few days is typical. This model forecastssmaller features, such as, individual showers and thunderstorms withreasonable accuracy, as well as other microscale phenomena. Fine-grainedweather models have two important features—a defined geographic regionand defined time period. From online URL(http://en.wikipedia.org/wiki/Microscale_meteorology)—“Microscalemeteorology is the study of short-lived atmospheric phenomena smallerthan mesoscale, about 1 km or less. These two branches of meteorologyare sometimes grouped together as “mesoscale and microscale meteorology”(MMM) and together study all phenomena smaller than synoptic scale; thatis they study features generally too small to be depicted on a weathermap. These include small and generally fleeting cloud “puffs” and othersmall cloud features. Microscale meteorology controls the most importantmixing and dilution processes in the atmosphere. Important topics inmicroscale meteorology include heat transfer and gas exchange betweensoil, vegetation, and/or surface water and the atmosphere caused bynear-ground turbulence. Measuring these transport processes involves useof micrometeorological (or flux) towers. Variables often measured orderived include net radiation, sensible heat flux, latent heat flux,ground heat storage, and fluxes of trace gases important to theatmosphere, biosphere, and hydrosphereish explained.”

The term “geographic region” means a defined portion of the world. Adestination region could be any small pre-defined geographic regionincluding a postal code, a stadium, or an area defined by globalposition system (GPS) coordinates, in which lift data for a flight pathis used.

The term “lift” is the force that directly opposes the weight of anairplane and holds the airplane in the air. Lift is generated by everypart of the airplane, but most of the lift on a normal airliner isgenerated by the wings. See online website(http://www.grc.nasa.gov/WWW/k-12/airplane/liftl.html). Soaring aircraftand soaring birds use lift as an energy source to stay aloft.

The term “lift data” means data from weather and sensor and includesdata wherein the lift data includes at least one of: 1) thermal liftdata where air rises due to temperature, 2) ridge lift data where air isforced upwards by a slope, 3) wave lift data where a mountain produces astanding wave, 4) convergence lift data where two air masses meet, and5) a dynamic soaring lift data where differences in wind speeds atvarious altitudes is used.

The term “sensor” is a device that can measure physical attributes ofexternal environmental converting readings of light, motion,temperature, magnetic fields, gravity, humidity, moisture, vibration,pressure, electrical fields, sound, and other physical aspects of theexternal environment into values related to lift data that is usable bya computer. Lift data is derived from measuring heat transfer and gasexchange between soil, vegetation, and/or surface water and theatmosphere caused by near-ground turbulence. Variables often measured orderived include net radiation, sensible heat flux, latent heat flux,ground heat storage, and fluxes of trace gases important to theatmosphere, biosphere, and hydrosphere.

The term “time period” means a duration, such as those measured inminutes, in which a lift data is deemed relevant.

Lift Sources

Referring to FIG. 1, shown is a diagram 100 of a soaring aircraft 102using thermal lift. Thermal lift is dependent on solar energy and therelative heating of surface structures. In this example, the generalwind direction is shown moving from left to right 132, 134, 136. Threegeographic features of a farm with a plowed field 120, a marsh 122 and atown 124 are shown. Better lift 140 is forecasted and/or measured over aplowed field 120 as shown. Poorer lift is forecasted and/or measuredover marsh 122. The better lift 144 is again forecasted and/or measuredover a town 124 as shown. Lift sometimes can be predicted based on cloudtype. Shown above each geographic region is a stage of formation ofcumulus cloud. Specifically, geographic region over the plowed field 120has a new cumulus cloud formation 150. The geographic region over themarsh 122 illustrates a decayed cumulus cloud formation 152. And theregion over the town 124 illustrates a mature cumulus cloud formation154.

FIG. 2 is a diagram 200 of a soaring aircraft 202 using ridge lift 240also known as slope lift. Ridge lift is dependent on wind blowingagainst a geographic feature should as a mountain, hill, cliff or ridgeline. Again, in this example, the general wind direction is shown movingfrom left to right 232, 234, 236. In this example the wind is deflectedupward because of the ridge line 220.

FIG. 3 is a diagram 300 of a soaring aircraft 302 using convergence lift340. Convergence lift is dependent on wind or air massing blowing indifferent directions. In this example two air masses 332 and 334traveling in opposite directions are shown. As the air masses converge,convergence lift 340 is created. Again as in other types of liftdiscussed herein, cloud formations 350 may be used to help predictand/or measure this type of lift.

FIG. 4 is a diagram 400 of a soaring aircraft 402 using wave lift. Wavelift is dependent on wind blowing against a geographic feature should asa mountain, hill, cliff or ridge line, typically as speeds of more than25 miles per hour. The wind 432, 434, 436 flows over the top of themountain 420 or other obstruction and down the opposite side of themountain. The speed increases with altitude 440. On the leeward side ofthe mountain 420 the wind bounces off a layer of stable air 430 near theground and is deflected upward 442 many thousands of feet to stable airwhere it bounces downward again 444. This wave action can occur manytimes in succession 446, 448 and is very similar to what is observedwhen water flows over a submerged log in a stream.

FIG. 5 is a diagram 500 of a soaring aircraft 502 using dynamic lift.Using dynamic lift, also called dynamic soaring, the energy is gained byrepeatedly crossing the boundary between air masses of differenthorizontal velocity rather than by rising air. Such zones of high “windgradient” are usually too close to the ground to be used safely bygliders. In this example, the general wind direction is shown movingfrom left to right 532, 534, 536 over the top of the ridge 520. Note theridge 520 is optional. It is important to note that boundaries betweendifferent air masses can occur without these mountain geographicfeatures. On the leeward side of the mountain 524, the wind near theground 540 is dead or still. A boundary 542 is created between thedifferent air masses layers as shown.

Flight Path Communications

FIG. 6 is an example 600 of three aircraft 602, 604, 606 sharing liftdata from various sources. To begin only one of the aircraft 602, 604,606 may be updating a flight path according to the claimed invention.The other aircraft could be flying routes not using flight pathinformation disclosed herein. For simplicity, assume aircraft 602 is notusing a flight path determined by the presently claimed invention.Rather, aircraft 602 is sharing lift data over wireless communicationlink 612 back to soaring aircraft 604, which in turn is sharing liftdata over wireless communication link 626 to aircraft 606. Theinformation shared can be from one or more onboard sensors (not shown)on aircraft 602. Soaring aircraft 604 and 606 are each showncommunicating with ground weather stations 640 over wirelesscommunication link 624 and 642 over wireless communication link 630,respectively. These ground stations can provide lift related dataincluding weather data. Also shown is an alternative communication to asatellite 650 over wireless communications links 622, 628, and 634. Allof this can be shared over a global network with a base station 662 forassisting with flight path calculations and storage of previous flightpaths. Lift data may be stored temporarily or permanently on aircraft604 and aircraft 606, at base stations 662, or a combination of thereof.As shown by the arrows in FIG. 6, aircraft 604 and aircraft 606 andground weather stations 640, 642 communicate lift data throughout itsflight such that on aircraft 604 and aircraft 606. Lift data is derivedfrom measuring heat transfer and gas exchange between soil, vegetation,and/or surface water and the atmosphere caused by near-groundturbulence. Variables often measured or derived include net radiation,sensible heat flux, latent heat flux, ground heat storage, and fluxes oftrace gases important to the atmosphere, biosphere, and hydrosphere.

Lift data is also received from ground weather stations 640, 642.Aircraft 604 and aircraft 606 also relay such atmospheric informationdata to satellites 650, which also communicate with ground weatherstations 640, 642. In addition, aircraft 604 and aircraft 606 may alsorelay such data to one or more other aircraft 602 in order to coordinateflights paths and/or locations, share atmospheric information data, andavoid collisions or overcrowding an airspace. This continuous andcontemporaneous relay of atmospheric information between aircraft 604and aircraft 606, atmospheric information ground weather stations 640,642, satellite 650 and base station 662 constitutes in part anatmospheric data network 662.

FIG. 7 is a diagram 700 of the major sources of data input for a flightpath processor 714. The flight processor 714 equipped with communicatingover network link 744 to network 730, that is, receive, process,transmit, relay and the like. Shown communicatively coupled to thenetwork 730 is lift data from onboard sensor from aircraft 604 and 606.Lift data from crowdsourcing data 706 is also coupled to the network730. Also shown is lift data from other aircraft 712 and lift data froma ground weather station or weather tower 714. The flight path processor714 is connected to network 730, e.g., the Internet or a local areanetwork 730.

The links 722, 724, 726, 742, 744, 746, 748, 750 may be directly orindirectly coupled to network 730. For example, hardwired networkconnection or wirelessly coupled to network 730 via wirelesscommunication channel. Although many aspects are shown as discretesystems, it is within the true scope and spirit of the presently claimedinvention for these to be combined into one system.

The flight path processor 714 may include, but are not limited to: apersonal computer, a server computer, a series of server computers, amini computer, and a mainframe computer. The flight path processor 714may be a single server or a series of servers running a networkoperating system, examples of which may include but are not limited toMicrosoft Windows Server or Linux. The flight path processor 714 mayexecute a web server application, examples of which may include but arenot limited to IBM Websphere or Apache Webserver™, that allows for HTTP(i.e., HyperText Transfer Protocol) access to other systems via network730. Moreover, network 730 may be connected to one or more secondarynetworks e.g., network 730, examples of which may include but are notlimited to: a local area network; a wide area network; or an intranet,for example. Three important inputs 750 to the flight path processor 714are shown. These inputs include 1) Geographic Location (GL), 2)Geographic Range (GR), and 3) Time Period (TP). The flight pathprocessor uses these inputs along with the lift data sources 1, 2, 3 . .. (LDS1, LDS2, LDS3, . . . ) in a function f(GL, GR, TP, LDS1, LDS2,LDS3, . . . ) may include using history and machine learning algorithms,such as Bayesian algorithms and neural networks. The machine learningalgorithms can include both supervised and unsupervised algorithms.

The flight path processor calculates routes in three main steps asfollow:

-   -   1) Generate estimates of sensible “average” values for the climb        rate and maximum height of each thermal using the fine-grained        weather model. The term sensible means to throw out any values        that are beyond a given standard deviation. For a more        conservative approach, these “averages” values should be close        to minima.    -   2) Calculate approximate times to get from any thermal to the        goal point. Using the average values for climb rates and maximum        heights, calculate the travel time between pairs of thermals.        This will consist of the time taken to rise to a suitable height        at the first thermal as well as the travel time to the second        thermal. These approximations determine which regions of space        are most promising by calculating the shortest path from each        node to the end node. This can be done using a single shortest        path calculation from the end point.    -   3) Use the approximate times combined with detailed information        about the points which are close by in space and time to choose        where to go next. While flying to a thermal, calculate the        quickest path from this thermal to the end node in a more        detailed network. The more detailed network includes multiple        nodes for all thermals, discretized across both time and        heights. The approximations found in the previous step can be        added to the paths found in order to rank paths and to ensure        that full paths are always known. When a new path is required,        the best one found so far is used to choose the next thermal to        fly towards. The choice of flight path could incorporate        previously computed flight paths in order to estimate flight        path reliability.

Lift Data

FIG. 8 is a table 800 of lift data used with by the flight pathprocessor 714. As shown a column with a lift data source 802 is uniquelyidentified. A column of the type of lift 804 along with a geographicregion 806, column 808 with a geographic range, and column 810 is thetime period of the forecast. For example in row 832 a WEATHER SERVICE isthe source of the lift data for a THERMAL LIFT, for a specificgeographic location, with a geographic range of 0.5 KM for 300 minutes.Likewise, in row 844, shown is a WEATHER TOWER providing the course ofthe lift data, the type of lift is a dynamic lift, for a same geographiclocation as shown in row 832, however the geographic range is only 0.3KM and the time 30 minutes.

Flow Chart

FIG. 9 is a flow chart of is a flow chart 900 of processing lift data800 by the flight path processor 714. The process begins in step 902 andimmediately proceeds to step 904 in which a flight path of an aircraftis computed or pre-computed from a starting point to an ending pointwhich incorporates predicted weather effects at different points inspace and time. Step 904 is a first step of an iterative loop of steps904 through 916. Specifically, the first step 906 in the iterative loop,lift data from a fine-grained weather model associated with a geographicregion of interest is accessed. The lift data is data to calculate aforce that directly opposes a weight of the aircraft. Next, in step 908,lift data is accessed from one or more sensors coupled to the aircraft.In step 910, adjustments to the flight path are computed based on acombination of the lift data from the fine-grained weather model and thelift data from the sensors. Step 912 adjustments are computed to theflight path based on a combination of the lift data from the fine-grainweather model and the lift data from sensors. A test is made if theflight is completed in step 914. If the flight is completed, then theprocess ends in step 916. Otherwise, while the flight is underway thenext step 918 is to test if the flight has indeed begun. If the flighthas begun in step 918 then the process loops back to step 904.Otherwise, if the flight has not yet begun in step 918, a test is madeto determine if the flight is ready for takeoff in step 920. If theflight is not ready for takeoff then the process loops back to step 904.Otherwise, the flow continues where the flight takes off in step 924,and the process returns to the iterative loop of step 904 as shown.

Information Processing System

Referring now to FIG. 10, this figure is a block diagram 1000illustrating an information processing system that can be utilized inembodiments of the present invention for flight path processor 714. Anysuitably configured processing system can be used as the informationprocessing system 1002 in embodiments of the present invention. Thecomponents of the information processing system 1002 can include, butare not limited to, one or more processors or processing units 1004, asystem memory 1006, and a bus 1008 that couples various systemcomponents including the system memory 1006 to the processor 1004. Thesystem memory 1006 can include the computer code for the flight pathprocessor 1030 as well as the lift data table 1032 of FIG. 8.

The bus 1008 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

The information processing system 1002 can further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, a storage system 1014 can be provided forreading from and writing to a non-removable or removable, non-volatilemedia such as one or more solid state disks and/or magnetic media(typically called a “hard drive”). A magnetic disk drive for readingfrom and writing to a removable, non-volatile magnetic disk (e.g., a“floppy disk”), and an optical disk drive for reading from or writing toa removable, non-volatile optical disk such as a CD-ROM, DVD-ROM orother optical media can be provided. In such instances, each can beconnected to the bus 1008 by one or more data media interfaces. Thememory 1006 can include at least one program product having a set ofprogram modules that are configured to carry out the functions of anembodiment of the present invention.

Program/utility 1016, having a set of program modules 1018, may bestored in memory 1006 by way of example, and not limitation, as well asan operating system, one or more application programs, other programmodules, and program data. Each of the operating system, one or moreapplication programs, other program modules, and program data or somecombination thereof, may include an implementation of a networkingenvironment. Program modules 1018 generally carry out the functionsand/or methodologies of embodiments of the present invention.

The information processing system 1002 can also communicate with one ormore external devices 1020 such as a keyboard, a pointing device, adisplay 1022, etc.; one or more devices that enable a user to interactwith the information processing system 1002; and/or any devices (e.g.,network card, modem, etc.) that enable computer system/server 1002 tocommunicate with one or more other computing devices. Such communicationcan occur via I/O interfaces 1024. Still yet, the information processingsystem 1002 can communicate with one or more networks such as a localarea network (LAN), a general wide area network (WAN), and/or a publicnetwork (e.g., the Internet) via network adapter 1026. As depicted, thenetwork adapter 1026 communicates with the other components ofinformation processing system 1002 via the bus 1008. Other hardwareand/or software components can also be used in conjunction with theinformation processing system 1002. Examples include, but are notlimited to: microcode, device drivers, redundant processing units,external disk drive arrays, RAID systems, tape drives, and data archivalstorage systems.

Non-Limiting Examples

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method, or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention have been discussed above withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems) and computer program products according to variousembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The description of the present application has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the invention in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.The embodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A computer-implemented method for adjusting aflight path of an aircraft, the method comprising: computing a flightpath of an aircraft from a starting point to an ending point whichincorporates predicted weather effects at different points in space andtime; during a flight path performing each of: accessing lift data froma fine-grained weather model associated with a geographic region ofinterest, the lift data being data to calculate a force that directlyopposes a weight of the aircraft; accessing lift data from sensorscoupled to the aircraft; computing adjustments to the flight path basedon a combination of the lift data from the fine-grain weather model andthe lift data from sensors; and adjusting the flight path using theadjustments that have been computed.
 2. The computer-implemented methodof claim 1, wherein the lift data includes at least one of thermal lift,ridge lift, wave lift, convergence lift, and a dynamic soaring lift. 3.The computer-implemented method of claim 1, wherein the adjusting theflight path based on a combination of the lift data from thefine-grained weather model and the lift data from sensors furtherincludes using lift data from crowdsourcing data.
 4. Thecomputer-implemented method of claim 1, further comprising: sending theflight path as it is adjusted to a second aircraft.
 5. Thecomputer-implemented method of claim 4, further comprising: receivingadjustments to the flight path from the second aircraft in order toavoid collisions therewith.
 6. The computer-implemented method of claim1, wherein the computing adjustments to the flight path is performed ona second aircraft.
 7. The computer-implemented method of claim 1,wherein at least a portion of the computing adjustments to the flightpath is performed by a second aircraft.
 8. The computer-implementedmethod of claim 1, wherein the aircraft is unpowered.
 9. Thecomputer-implemented method of claim 1, wherein the aircraft is poweredby one or more engines.
 10. The computer-implemented method of claim 1,wherein at least one of computing a flight path of an aircraft from thestarting point to the ending point, and adjusting the flight path usingthe adjustments that have been computed, includes using a portion of theflight path that have previously computed
 11. An aircraft flight passprocessor system comprising: a memory; a processor communicativelycoupled to the memory, where the processor is configured to performcomputing a flight path of an aircraft from a starting point to anending point which incorporates predicted weather effects at differentpoints in space and time; during a flight path performing each of:accessing lift data from a fine-grain weather model associated with ageographic region of interest, the lift data being data to calculate aforce that directly opposes a weight of the aircraft; accessing liftdata from sensors coupled to the aircraft; computing adjustments to theflight path based on a combination of the lift data from the fine-grainweather model and the lift data from sensors; and adjusting the flightpath using the adjustments that have been computed.
 12. The aircraftflight path processor system of claim 11, wherein the lift data includesat least one of thermal lift, ridge lift, wave lift, convergence lift,and a dynamic soaring lift.
 13. The aircraft flight path processorsystem of claim 11, wherein the adjusting the flight path based on acombination of the lift data from the fine-grained weather model and thelift data from sensors further includes using lift data fromcrowdsourcing data.
 14. The aircraft flight path processor system ofclaim 11, further comprising: sending the flight path as it is adjustedto a second aircraft.
 15. The aircraft flight path processor system ofclaim 14, further comprising: receiving adjustments to the flight pathfrom the second aircraft in order to avoid collisions therewith.
 16. Theaircraft flight path processor system of claim 11, wherein the computingadjustments to the flight path is performed on a second aircraft. 17.The aircraft flight path processor system of claim 11, wherein at leasta portion of the computing adjustments to the flight path is performedby a second aircraft.
 18. The aircraft flight path processor system ofclaim 11, wherein the aircraft is powered by one or more engines. 19.The aircraft flight path processor system of claim 11, wherein at leastone of computing a flight path of an aircraft from the starting point tothe ending point, and adjusting the flight path using the adjustmentsthat have been computed, includes using a portion of the flight paththat have previously computed
 20. A computer program product foradjusting flight path of an aircraft, the computer program productcomprising a computer readable storage medium having program codeembodied therewith, the program code executable on processor to perform:computing a flight path of an aircraft from a starting point to anending point which incorporates predicted weather effects at differentpoints in space and time; during a flight path performing each of:accessing lift data from a fine-grain weather model associated with ageographic region of interest, the lift data being data to calculate aforce that directly opposes a weight of the aircraft; accessing liftdata from sensors coupled to the aircraft; computing adjustments to theflight path based on a combination of the lift data from the fine-grainweather model and the lift data from sensors; and adjusting the flightpath using the adjustments that have been computed.